Machine learning is a technique that examines a set of instances each having an associated value or class to learn a concept. The set of instances and the associated values are often referred to as a training data set. Having learned the concept, it may then be applied to a new instance to predict a value or class for the new instance. The technique is referred to as “machine” learning because it employs a computer (i.e., a machine).
Machine learning techniques such as regression, classification trees, and decision trees are applied to an entire training data set. Applying these techniques to an entire training data set may make it more difficult to predict values. A standard technique used in data mining and statistics is to eliminate outliers from a training data set. The outliers are determined by identifying unusual values in the training data set. The outliers are then removed from the training data set. Such a technique does not address predictability.